AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...

Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications. The convergence of ...

Researchers from The University of Osaka's Institute of Scientific and Industrial Research (SANKEN) have successfully ...

SLMs targeted at specific workloads could change the relationship between edge devices and the cloud, creating new ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. From IoT and robotics to industrial automation and smart devices, AI is fundamentally ...

Edgeble AI enables industrial robots, cameras, and autonomous vehicles to detect accuracy drift and retrain AI models ...

SAN JOSE, Calif.--(BUSINESS WIRE)--Edge Impulse, the leading platform for building, deploying, and scaling edge machine learning models, today announces Microchip Technology’s SAMA7G54 microprocessor ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. The AI landscape is taking a dramatic turn, as small language and multimodal models are ...

Ask virtually anyone what's happening in the tech industry right now, and you'll hear the same answer: the AI is coming, the AI is coming. But ...